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In this article a multiple regime extension for the Heston-Nandi GARCH(1,1) model is presented to describe the asymmetries and intermittent dynamics in financial volatility. The statistical properties and the estimation of their parameters are addressed in detail. The number of regimes in the model is determined through a statistical procedure based on a novel robust Lagrange Multiplier (LM) specification. The ability of the model to forecast financial market volatility is empirically compared to other GARCH models for a set comprising some of the major world stock indexes and their corresponding foreign exchange rates during the recent financial crisis

A Multiple Regime Nonlinear Asymmetric AR(p)-GARCH(1,1) Model